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From spontaneous motor activity to coordinated behaviour: a developmental model.

Marques HG, Bharadwaj A, Iida F - PLoS Comput. Biol. (2014)

Bottom Line: Our model is tested in a simulated musculoskeletal leg actuated by six muscles arranged in a number of different ways.Hopping is used as a case study of coordinated behaviour.In addition, our results show that our model can naturally adapt to different morphological changes and perform behavioural transitions.

View Article: PubMed Central - PubMed

Affiliation: Dept. of Mechanical and Process Engineering, ETH, Zurich, Switzerland.

ABSTRACT
In mammals, the developmental path that links the primary behaviours observed during foetal stages to the full fledged behaviours observed in adults is still beyond our understanding. Often theories of motor control try to deal with the process of incremental learning in an abstract and modular way without establishing any correspondence with the mammalian developmental stages. In this paper, we propose a computational model that links three distinct behaviours which appear at three different stages of development. In order of appearance, these behaviours are: spontaneous motor activity (SMA), reflexes, and coordinated behaviours, such as locomotion. The goal of our model is to address in silico four hypotheses that are currently hard to verify in vivo: First, the hypothesis that spinal reflex circuits can be self-organized from the sensor and motor activity induced by SMA. Second, the hypothesis that supraspinal systems can modulate reflex circuits to achieve coordinated behaviour. Third, the hypothesis that, since SMA is observed in an organism throughout its entire lifetime, it provides a mechanism suitable to maintain the reflex circuits aligned with the musculoskeletal system, and thus adapt to changes in body morphology. And fourth, the hypothesis that by changing the modulation of the reflex circuits over time, one can switch between different coordinated behaviours. Our model is tested in a simulated musculoskeletal leg actuated by six muscles arranged in a number of different ways. Hopping is used as a case study of coordinated behaviour. Our results show that reflex circuits can be self-organized from SMA, and that, once these circuits are in place, they can be modulated to achieve coordinated behaviour. In addition, our results show that our model can naturally adapt to different morphological changes and perform behavioural transitions.

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The hip trajectory and the mean and standard deviation of the kinematic and dynamic variables obtained for the default modified models using dynamic gain modulation.Kinematic and dynamic variables obtained for the system with a) misplaced  and b) misplaced  S refers to the stance phase (when the end effector is in touch with the ground) and F refers to the flight phase (when the end effector is in the air). The hip trajectory recorded for the system with c) misplaced  and d) misplaced
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pcbi-1003653-g012: The hip trajectory and the mean and standard deviation of the kinematic and dynamic variables obtained for the default modified models using dynamic gain modulation.Kinematic and dynamic variables obtained for the system with a) misplaced and b) misplaced S refers to the stance phase (when the end effector is in touch with the ground) and F refers to the flight phase (when the end effector is in the air). The hip trajectory recorded for the system with c) misplaced and d) misplaced

Mentions: Next, the importance of the gain tuning is examined through the case study, which was not fully successful in the previous section, i.e. the one with the modified In Figure 12a,c one can observe the hopping pattern obtained in this system using one set of parameters for each movement phase. Using the new strategy, one can still observe oscillations during the hopping cycle due to the lack of a bi-articular muscle on the posterior part of the leg (Figure 12a). However, when analysing the hopping height achieved we can observe that it is now stable across different hops ( and this contrasts with Figure 9f in which the hopping height changed considerably from one hop to the next To show the generality of our results we show an additional modification of the mechanical system, in which the is placed parallel to the (see also Movie S1.VI). Similarly to the modification of the we could not obtain a stable hopping pattern for this system with a single set of gains. Our results are shown in Figure 12b,d (see also Movie S1.VI). With the exception of the muscle oscillations, which are considerably reduced in this system, we obtained very similar results when compared to the system with the modified ().


From spontaneous motor activity to coordinated behaviour: a developmental model.

Marques HG, Bharadwaj A, Iida F - PLoS Comput. Biol. (2014)

The hip trajectory and the mean and standard deviation of the kinematic and dynamic variables obtained for the default modified models using dynamic gain modulation.Kinematic and dynamic variables obtained for the system with a) misplaced  and b) misplaced  S refers to the stance phase (when the end effector is in touch with the ground) and F refers to the flight phase (when the end effector is in the air). The hip trajectory recorded for the system with c) misplaced  and d) misplaced
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4109855&req=5

pcbi-1003653-g012: The hip trajectory and the mean and standard deviation of the kinematic and dynamic variables obtained for the default modified models using dynamic gain modulation.Kinematic and dynamic variables obtained for the system with a) misplaced and b) misplaced S refers to the stance phase (when the end effector is in touch with the ground) and F refers to the flight phase (when the end effector is in the air). The hip trajectory recorded for the system with c) misplaced and d) misplaced
Mentions: Next, the importance of the gain tuning is examined through the case study, which was not fully successful in the previous section, i.e. the one with the modified In Figure 12a,c one can observe the hopping pattern obtained in this system using one set of parameters for each movement phase. Using the new strategy, one can still observe oscillations during the hopping cycle due to the lack of a bi-articular muscle on the posterior part of the leg (Figure 12a). However, when analysing the hopping height achieved we can observe that it is now stable across different hops ( and this contrasts with Figure 9f in which the hopping height changed considerably from one hop to the next To show the generality of our results we show an additional modification of the mechanical system, in which the is placed parallel to the (see also Movie S1.VI). Similarly to the modification of the we could not obtain a stable hopping pattern for this system with a single set of gains. Our results are shown in Figure 12b,d (see also Movie S1.VI). With the exception of the muscle oscillations, which are considerably reduced in this system, we obtained very similar results when compared to the system with the modified ().

Bottom Line: Our model is tested in a simulated musculoskeletal leg actuated by six muscles arranged in a number of different ways.Hopping is used as a case study of coordinated behaviour.In addition, our results show that our model can naturally adapt to different morphological changes and perform behavioural transitions.

View Article: PubMed Central - PubMed

Affiliation: Dept. of Mechanical and Process Engineering, ETH, Zurich, Switzerland.

ABSTRACT
In mammals, the developmental path that links the primary behaviours observed during foetal stages to the full fledged behaviours observed in adults is still beyond our understanding. Often theories of motor control try to deal with the process of incremental learning in an abstract and modular way without establishing any correspondence with the mammalian developmental stages. In this paper, we propose a computational model that links three distinct behaviours which appear at three different stages of development. In order of appearance, these behaviours are: spontaneous motor activity (SMA), reflexes, and coordinated behaviours, such as locomotion. The goal of our model is to address in silico four hypotheses that are currently hard to verify in vivo: First, the hypothesis that spinal reflex circuits can be self-organized from the sensor and motor activity induced by SMA. Second, the hypothesis that supraspinal systems can modulate reflex circuits to achieve coordinated behaviour. Third, the hypothesis that, since SMA is observed in an organism throughout its entire lifetime, it provides a mechanism suitable to maintain the reflex circuits aligned with the musculoskeletal system, and thus adapt to changes in body morphology. And fourth, the hypothesis that by changing the modulation of the reflex circuits over time, one can switch between different coordinated behaviours. Our model is tested in a simulated musculoskeletal leg actuated by six muscles arranged in a number of different ways. Hopping is used as a case study of coordinated behaviour. Our results show that reflex circuits can be self-organized from SMA, and that, once these circuits are in place, they can be modulated to achieve coordinated behaviour. In addition, our results show that our model can naturally adapt to different morphological changes and perform behavioural transitions.

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